Biomedical Data Analyst

Unnati Agarwal

602-***-**** ********@***.*** LinkedIn

TECHNICAL SKILLS

Programming & Data Analysis: Python (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow, Keras, Matplotlib, Seaborn, PyRadiomics, Nibabel, OpenCV, Gensim), SQL, SAS, Tableau, Power BI. Machine Learning & AI: Supervised Learning (Random Forest, SVM, Logistic Regression), Unsupervised Learning (Clustering, PCA), Deep Learning (CNN, RNN, Transformers), Computer Vision, Image Segmentation and Radiomics Feature Extraction, Predictive Modelling, NLP Pipelines (TF-IDF/Word2Vec), Neural Networks. Healthcare Analytics: Predictive modelling, Claims Analysis, Utilization Management, Cost of Care Analysis, Trend Analysis, Financial Modelling, ROI Evaluation, Risk Stratification Healthcare Domain Knowledge: Medical Economics, Claims Payment Processes, Population Health, Predictive Data Modelling, Trend Analysis, Root-Cause Analysis, Regression Analysis PROFESSIONAL EXPERIENCE

Research Assistant Mayo Clinic (PI: Dr. Imon Banerjee) Phoenix, AZ May 2025 – Present

• Developed CNN-based segmentation models with PyRadiomics for automated feature extraction from CT imaging data and Conducted EDA and creating visualizations to identify patterns, trends, and anomalies in imaging and clinical datasets based on the segmentation.

• Automated segmentation and feature extraction workflows using Python, reducing manual processing time for translational research imaging pipelines ensuring 100% data integrity and HIPAA compliance.

• Managed data verification and integration of large-scale clinical datasets, collaborating with radiologists to ensure algorithm accuracy and research validity.

Analytics and Data Science Intern Blue Cross Blue Shield of Arizona Phoenix, AZ October 2025 – Present

• Performed quantitative analysis and data mining on Medicaid administrative data to conduct root-cause analysis of healthcare cost drivers, supporting corporate cost-containment strategies.

• Executed multivariate regression and data modelling for population risk stratification and provider contracting support, ensuring data verification across diverse clinical datasets.

• Engineered Business Intelligence visualization tools in Tableau and Power BI to communicate actionable insights on clinical outcomes to senior healthcare administrators.

Senior Research Analyst Wonder Engineering & Research India (Remote) December 2023 – July 2024

• Led cross-functional teams processing large-scale genomic and clinical datasets using Python and SQL, delivering 100% on-time project completion; automated data pipelines reducing analysis time by 43% through scripted workflows

• Performed complex data mining and statistical analysis to identify therapeutic trends, applying quantitative methods including trend analysis, data modelling, and root-cause analysis to inform precision medicine strategies Research Analyst GreyB Research India (Remote) July 2022 – October 2023

• Delivered comprehensive research and competitive intelligence analysis on healthcare technologies, medical devices, and market trends for biotechnology and pharmaceutical clients

• Developed financial models and ROI evaluations for healthcare technologies, managing multiple analytical projects simultaneously with limited supervision in demanding, fast-paced environment EDUCATION

• Master of Science in Biomedical Informatics & Data Science (May 2026) Arizona State University GPA: 4.00/4.00 Relevant Coursework: Machine learning, Health Economics and Policy, Statistical Learning, Disease Prediction, Statistical Analysis

• Bachelor of Technology in Biotechnology (May 2022) Lovely Professional University, India GPA: 8.20/10.00 KEY ANALYTICAL PROJECTS

• Healthcare Cost & Utilization Analysis Developed comprehensive analytical framework to assess Medicaid utilization patterns, identifying opportunities for cost reduction while maintaining quality of care; created automated reporting processes using SQL and Power BI

• Arizona Healthcare Disparities Dashboard Built interactive web-based analytics platform integrating Census, CDC, NPPES, and state health datasets to compute healthcare need scores; by geographic area; enabled data-driven resource allocation and policy decisions

• Predictive Modelling for Clinical Outcomes Conducted exploratory data analysis and creating visualizations to identify patterns, trends, and anomalies in imaging and clinical datasets based on the segmentation.

• Clinical Workflow Optimization Conducted process analysis using Lean and TPS A3 methodologies to identify operational inefficiencies in healthcare delivery; proposed automation solutions that reduced data processing time by 50%+ PUBLICATIONS & PROFESSIONAL ACHIEVEMENTS

• Co-authored 4 peer-reviewed publications in healthcare analytics and biomedical research (Neuro-Oncology Advances, AIP Conference Proceedings, Gels)

• Dean’s Recognition for Research Excellence, Arizona State University (May 2025)

• Member: American Medical Informatics Association (AMIA), Healthcare Information & Management Systems Society (HIMSS)

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